U.S. patent application number 16/481434 was filed with the patent office on 2020-04-16 for activity state analysis device and method.
The applicant listed for this patent is NIPPON TELEGRAPH AND TELEPHONE CORPORATION. Invention is credited to Hiroki MORIMURA, Hiroshi NAKASHIMA, Takayuki OGASAWARA, Shoichi OSHIMA, Rieko SATO, Shingo TSUKADA.
Application Number | 20200113490 16/481434 |
Document ID | / |
Family ID | 62979274 |
Filed Date | 2020-04-16 |
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United States Patent
Application |
20200113490 |
Kind Code |
A1 |
OGASAWARA; Takayuki ; et
al. |
April 16, 2020 |
ACTIVITY STATE ANALYSIS DEVICE AND METHOD
Abstract
A measurement unit is attached to a measurement target person
and measures an acceleration. A body motion calculation unit
obtains the magnitude of a body motion of the measurement target
person based on the acceleration measured by the measurement unit.
An activity state determination unit time-serially obtains an
activity state representing whether the measurement target person
is in a first state or a second state, based on a posture decided
by a posture decision unit and the magnitude of the body motion
calculated by the body motion calculation unit. If the activity
state after continues for a predetermined time defined in advance,
an activity state correction unit determines that the transition of
the activity state obtained by the activity state determination
unit has been done. A time correction unit returns the transition
time of the activity state determined by the activity state
correction unit.
Inventors: |
OGASAWARA; Takayuki; (Tokyo,
JP) ; TSUKADA; Shingo; (Tokyo, JP) ; OSHIMA;
Shoichi; (Tokyo, JP) ; MORIMURA; Hiroki;
(Tokyo, JP) ; NAKASHIMA; Hiroshi; (Tokyo, JP)
; SATO; Rieko; (Tokyo, JP) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
NIPPON TELEGRAPH AND TELEPHONE CORPORATION |
Tokyo |
|
JP |
|
|
Family ID: |
62979274 |
Appl. No.: |
16/481434 |
Filed: |
January 22, 2018 |
PCT Filed: |
January 22, 2018 |
PCT NO: |
PCT/JP2018/001740 |
371 Date: |
July 26, 2019 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A61B 5/1116 20130101;
A61B 5/0002 20130101; A61B 5/112 20130101; A61B 5/1118 20130101;
A61B 5/4809 20130101; A61B 5/024 20130101; A61B 5/107 20130101;
A61B 5/11 20130101; A61B 5/7282 20130101; A61B 2562/0219 20130101;
A61B 5/0205 20130101; G16H 40/63 20180101 |
International
Class: |
A61B 5/11 20060101
A61B005/11; A61B 5/0205 20060101 A61B005/0205; A61B 5/00 20060101
A61B005/00 |
Foreign Application Data
Date |
Code |
Application Number |
Jan 30, 2017 |
JP |
2017-013964 |
Claims
1. An activity state analysis device comprising: a measurement unit
attached to a measurement target person and configured to measure
an acceleration; a tilt calculation unit configured to obtain an
angle of a tilt of an upper part of a body of the measurement
target person based on the acceleration measured by the measurement
unit; a posture decision unit configured to decide a posture of the
measurement target person based on the angle of the tilt obtained
by the tilt calculation unit; a body motion calculation unit
configured to obtain a magnitude of a body motion of the
measurement target person based on the acceleration measured by the
measurement unit; an activity state determination unit configured
to determine, based on the posture decided by the posture decision
unit and the magnitude of the body motion calculated by the body
motion calculation unit, whether an activity state of the
measurement target person is a first state or a second state
different from the first state; an activity state correction unit
configured to, if, in a time series of the activity state obtained
by the activity state determination unit, the activity state
transitions from one state of the first state and the second state
to the other state, and the other state continues for a
predetermined time defined in advance, determine that the activity
state has transitioned from the one state to the other state, and
if the other state does not continue for the predetermined time,
determine that the activity state has not transitioned from the one
state to the other state; and a time correction unit configured to,
if the activity state correction unit determines that the activity
state has transitioned from the one state to the other state, sets
a time returned by the predetermined time from a time at which the
activity state correction unit determines that the activity state
has transitioned from the one state to the other state to a
transition time at which the activity state has transitioned from
the one state to the other state.
2. The activity state analysis device according to claim 1, wherein
the measurement unit measures accelerations in three directions
along X-, Y-, and Z-axes that are orthogonal to each other.
3. The activity state analysis device according to claim 1, further
comprising: a walking pace calculation unit configured to obtain a
walking pace of the measurement target person based on the
acceleration measured by the measurement unit; and a walking period
specifying unit configured to specify, based on the walking pace of
the measurement target person obtained by the walking pace
calculation unit, a period of a walking state in which the
measurement target person has walked in a period of the first state
defined by the transition time corrected by the time correction
unit.
4. The activity state analysis device according to claim 1, further
comprising a data adjustment unit configured to down-sample
time-serially obtained data of the activity state including the
first state and the second state while assigning priority to each
state.
5. The activity state analysis device according to claim 4, further
comprising a data additional adjustment unit configured to
down-sample the time-series data of the activity state output from
the data adjustment unit while assigning priority to each
state.
6. The activity state analysis device according to claim 1, further
comprising: a physical information measurement unit configured to
measure physical information of the measurement target person; and
a statistic value calculation unit configured to obtain, based on
the activity state defined by the transition time corrected by the
time correction unit, a statistic value including at least one of
an average value, a median, a maximum value, a minimum value, a
standard deviation, a 75% level value, and a 25% level value of the
physical information measured by the physical information
measurement unit.
7. The activity state analysis device according to claim 1, further
comprising: a heart rate measurement unit configured to measure a
heart rate of the measurement target person; a motion intensity
calculation unit configured to calculate a motion intensity of the
measurement target person based on the heart rate calculated by the
heart rate measurement unit; and a statistic value calculation unit
configured to obtain, based on the activity state defined by the
transition time corrected by the time correction unit, a statistic
value including at least one of an average value, a median, a
maximum value, a minimum value, a standard deviation, a 75% level
value, and a 25% level value of the motion intensity obtained by
the motion intensity calculation unit.
8. The activity state analysis device according to claim 1, wherein
the first state is a rising state in which the measurement target
person gets up, and the second state is a lying state in which the
measurement target person is lying in a bed.
9. An activity state analysis method comprising: a first step of
measuring an acceleration in an action of a measurement target
person; a second step of obtaining an angle of a tilt of an upper
part of a body of the measurement target person based on the
acceleration measured in the first step; a third step of deciding a
posture of the measurement target person based on the angle of the
tilt obtained in the second step; a fourth step of obtaining a
magnitude of a body motion of the measurement target person based
on the acceleration measured in the first step; a fifth step of
determining, based on the posture decided in the third step and the
magnitude of the body motion calculated in the fourth step, whether
an activity state of the measurement target person is a first state
or a second state different from the first state; a sixth step of,
if, in a time series of the activity state obtained in the fifth
step, the activity state transitions from one state of the first
state and the second state to the other state, and the other state
continues for a predetermined time defined in advance, determining
that the activity state has transitioned from the one state to the
other state, and if the other state does not continue for the
predetermined time, determining that the activity state has not
transitioned from the one state to the other state; and a seventh
step of, if it is determined in the sixth step that the activity
state has transitioned from the one state to the other state,
setting a time returned by the predetermined time from a time at
which it is determined in the sixth step that the activity state
has transitioned from the one state to the other state to a
transition time at which the activity state has transitioned from
the one state to the other state.
10. The activity state analysis method according to claim 9,
wherein, in the first step, accelerations in three directions along
X-, Y-, and Z-axes that are orthogonal to each other are
measured.
11. The activity state analysis method according to claim 9,
further comprising: an eighth step of obtaining a walking pace of
the measurement target person based on the acceleration measured in
the first step; and a ninth step of specifying, based on the
walking pace of the measurement target person obtained in the
eighth step, a period of a walking state in which the measurement
target person has walked in a period of the first state defined by
the transition time corrected in the seventh step.
12. The activity state analysis method according to claim 9,
further comprising: a 10th step of measuring physical information
of the measurement target person; and an 11th step of obtaining,
based on the activity state defined by the transition time
corrected in the seventh step, a statistic value including at least
one of an average value, a median, a maximum value, a minimum
value, a standard deviation, a 75% level value, and a 25% level
value of the physical information measured in the 10th step.
13. The activity state analysis method according to claim 9,
further comprising: a 10th step of measuring a heart rate of the
measurement target person; an 11th step of calculating a motion
intensity of the measurement target person based on the heart rate
calculated in the 10th step; and a 13th step of obtaining, based on
the activity state defined by the transition time corrected in the
seventh step, a statistic value including at least one of an
average value, a median, a maximum value, a minimum value, a
standard deviation, a 75% level value, and a 25% level value of the
motion intensity obtained in the 11th step.
14. The activity state analysis method according to claim 9,
wherein the first state is a rising state in which the measurement
target person gets up, and the second state is a lying state in
which the measurement target person is lying in a bed.
Description
TECHNICAL FIELD
[0001] The present invention relates to an activity state analysis
device and method and, more particularly, to an activity state
analysis device and method for analyzing the activity state of a
measurement target person based on physical information measured by
a sensor attached to the measurement target person.
BACKGROUND ART
[0002] In recent years, there have been proposed techniques of
detecting the physical information of a user (measurement target
person) from a sensor attached to the measurement target person. As
one of such physical information measurement techniques, for
example, non-patent literature 1 proposes a technique of
calculating the posture of a measurement target person from
acceleration data measured by a three-axis acceleration sensor
configured to detect accelerations in three directions along X-,
Y-, and Z-axes, grasping a physical activity from the posture, and
making use of it for lifestyle investigations (see, for example, p.
67 of non-patent literature 1).
[0003] In non-patent literature 1, it is estimated based on the
average value of the three-axis accelerations whether the posture
of the measurement target person is a lying position or a standing
position. Furthermore, in non-patent literature 1, four directions
(LyingLeft, LyingRight, LyingFaceUp, and LyingFaceDown) are
calculated in the lying position, and the tilt angle of the state
of the measurement target person is calculated in the standing
position from the average value of the axes.
RELATED ART LITERATURE
Patent Literature
[0004] Patent Literature 1: Japanese Patent Laid-Open No.
2016-182160
Non-Patent Literature
[0004] [0005] Non-Patent Literature 1: "hitoe transmitter SDK API
manual" NTT DOCOMO, Inc., Nov. 14, 2016. [0006] Non-Patent
Literature 2: Ken Koda, "Meanings and Importance of Active Bed
Leaving and Exercise Load and Its Physiological Mechanism", Human
Resources Development Study Group for Community Rehabilitation,
2013,
http://wakayama-med-reha.com/wp-content/uploads/2013/12/31bc2df5f92f959aa-
abc9d676a556abe.pdf. [0007] Non-Patent Literature 3:
https://ja.wikipedia.org/wiki/
DISCLOSURE OF INVENTION
Problem to be Solved by the Invention
[0008] In the above-described technique of posture determination
using the acceleration sensor, however, if the measurement target
person takes an exceptional position at the time of data
acquisition, the determination is erroneously done.
[0009] For example, when the measurement target person in the
standing position bends forward only for several sec to re-tie the
shoelaces, the position is erroneously determined as lying face
down (LyingFaceDown) by the above-described technique. Such a
determination error may be allowed for an application purpose such
as motion capture but is considerably problematic in a case in
which the activity state of a body is measured with focus on the
continuation time of the state as in lifestyle investigations.
[0010] For example, in the field of rehabilitation, it has been
pointed out that adverse effects such as hypotension readily occurs
if a lying state continues, and the importance of a sitting
position/standing position is pointed out (non-patent literature
2). From such a viewpoint, focus is placed on the continuation
period of the activity state of a patient. In general, the temporal
scale of the continuation period is several hrs to several days or
several weeks. In the lifestyle investigations, the above-described
determination of lying face down, which is done at the time of
re-tying shoelaces, should be excluded as a temporary exception as
a disturbance in grasping the continuity because it may lead to
misunderstanding rather than giving convenience. As described
above, the conventional technique cannot be applied in a case of
measuring an activity state as a habit.
[0011] The present invention has been made to solve the
above-described problem, and has as its object more correctly
measure the activity state of a measurement target person with
focus on the lifestyle.
Means of Solution to the Problem
[0012] According to the present invention, there is provided an
activity state analysis device comprising a measurement unit
attached to a measurement target person and configured to measure
an acceleration, a tilt calculation unit configured to obtain an
angle of a tilt of an upper part of a body of the measurement
target person based on the acceleration measured by the measurement
unit, a posture decision unit configured to decide a posture of the
measurement target person based on the angle of the tilt obtained
by the tilt calculation unit, a body motion calculation unit
configured to obtain a magnitude of a body motion of the
measurement target person based on the acceleration measured by the
measurement unit, an activity state determination unit configured
to determine, based on the posture decided by the posture decision
unit and the magnitude of the body motion calculated by the body
motion calculation unit, whether an activity state of the
measurement target person is a first state or a second state
different from the first state, an activity state correction unit
configured to, if, in a time series of the activity state obtained
by the activity state determination unit, the activity state
transitions from one state of the first state and the second state
to the other state, and the other state continues for a
predetermined time defined in advance, determine that the activity
state has transitioned from the one state to the other state, and
if the other state does not continue for the predetermined time,
determine that the activity state has not transitioned from the one
state to the other state, and a time correction unit configured to,
if the activity state correction unit determines that the activity
state has transitioned from the one state to the other state, sets
a time returned by the predetermined time from a time at which the
activity state correction unit determines that the activity state
has transitioned from the one state to the other state to a
transition time at which the activity state has transitioned from
the one state to the other state.
[0013] In the above-described activity state analysis device, the
measurement unit may measure accelerations in three directions
along X-, Y-, and Z-axes that are orthogonal to each other.
[0014] The above-described activity state analysis device may
comprise walking pace calculation unit configured to obtain a
walking pace of the measurement target person based on the
acceleration measured by the measurement unit, and a walking period
specifying unit configured to specify, based on the walking pace of
the measurement target person obtained by the walking pace
calculation unit, a period of a walking state in which the
measurement target person has walked in a period of the first state
defined by the transition time corrected by the time correction
unit.
[0015] The above-described activity state analysis device may
further comprise a data adjustment unit configured to down-sample
time-serially obtained data of the activity state including the
first state and the second state while assigning priority to each
state.
[0016] The above-described activity state analysis device may
further comprise a data additional adjustment unit configured to
down-sample the time-series data of the activity state output from
the data adjustment unit while assigning priority to each
state.
[0017] The above-described activity state analysis device may
further comprise a physical information measurement unit configured
to measure physical information of the measurement target person,
and a statistic value calculation unit configured to obtain, based
on the activity state defined by the transition time corrected by
the time correction unit, a statistic value including at least one
of an average value, a median, a maximum value, a minimum value, a
standard deviation, a 75% level value, and a 25% level value of the
physical information measured by the physical information
measurement unit.
[0018] The above-described activity state analysis device may
further comprise a heart rate measurement unit configured to
measure a heart rate of the measurement target person, a motion
intensity calculation unit configured to calculate a motion
intensity of the measurement target person based on the heart rate
calculated by the heart rate measurement unit, and a statistic
value calculation unit configured to obtain, based on the activity
state defined by the transition time corrected by the time
correction unit, a statistic value including at least one of an
average value, a median, a maximum value, a minimum value, a
standard deviation, a 75% level value, and a 25% level value of the
motion intensity obtained by the motion intensity calculation
unit.
[0019] In the above-described activity state analysis device, the
first state is a rising state in which the measurement target
person gets up, and the second state is a lying state in which the
measurement target person is lying in a bed.
[0020] According to the present invention, there is also provided
an activity state analysis method comprising a first step of
measuring an acceleration in an action of a measurement target
person, a second step of obtaining an angle of a tilt of an upper
part of a body of the measurement target person based on the
acceleration measured in the first step, a third step of deciding a
posture of the measurement target person based on the angle of the
tilt obtained in the second step, a fourth step of obtaining a
magnitude of a body motion of the measurement target person based
on the acceleration measured in the first step, a fifth step of
determining, based on the posture decided in the third step and the
magnitude of the body motion calculated in the fourth step, whether
an activity state of the measurement target person is a first state
or a second state different from the first state, a sixth step of,
if, in a time series of the activity state obtained in the fifth
step, the activity state transitions from one state of the first
state and the second state to the other state, and the other state
continues for a predetermined time defined in advance, determining
that the activity state has transitioned from the one state to the
other state, and if the other state does not continue for the
predetermined time, determining that the activity state has not
transitioned from the one state to the other state, and a seventh
step of, if it is determined in the sixth step that the activity
state has transitioned from the one state to the other state,
setting a time returned by the predetermined time from a time at
which it is determined in the sixth step that the activity state
has transitioned from the one state to the other state to a
transition time at which the activity state has transitioned from
the one state to the other state.
[0021] In the above-described activity state analysis method, in
the first step, accelerations in three directions along X-, Y-, and
Z-axes that are orthogonal to each other are measured.
[0022] The above-described activity state analysis method may
further comprise an eighth step of obtaining a walking pace of the
measurement target person based on the acceleration measured in the
first step, and a ninth step of specifying, based on the walking
pace of the measurement target person obtained in the eighth step,
a period of a walking state in which the measurement target person
has walked in a period of the first state defined by the transition
time corrected in the seventh step.
[0023] The above-described activity state analysis method may
further comprise a 10th step of measuring physical information of
the measurement target person, and an 11th step of obtaining, based
on the activity state defined by the transition time corrected in
the seventh step, a statistic value including at least one of an
average value, a median, a maximum value, a minimum value, a
standard deviation, a 75% level value, and a 25% level value of the
physical information measured in the 10th step.
[0024] The above-described activity state analysis method may
further comprise a 10th step of measuring a heart rate of the
measurement target person, an 11th step of calculating a motion
intensity of the measurement target person based on the heart rate
calculated in the 10th step, and a 13th step of obtaining, based on
the activity state defined by the transition time corrected in the
seventh step, a statistic value including at least one of an
average value, a median, a maximum value, a minimum value, a
standard deviation, a 75% level value, and a 25% level value of the
motion intensity obtained in the 11th step.
[0025] In the above-described activity state analysis method, the
first state is a rising state in which the measurement target
person gets up, and the for example, is a lying state in which the
measurement target person is lying in a bed.
Effect of the Invention
[0026] As described above, according to the present invention, in
addition to the magnitude of the body motion obtained by the body
motion calculation unit, correction is performed when the state
after the transition continues for the predetermined time defined
in advance, and a delay caused by the correction is corrected. It
is therefore possible to obtain an excellent effect of more
correctly measuring the activity state of the measurement target
person with focus on the lifestyle.
BRIEF DESCRIPTION OF DRAWINGS
[0027] FIG. 1 is a block diagram showing the arrangement of an
activity state analysis device according to the first embodiment of
the present invention;
[0028] FIG. 2A is an explanatory view for explaining an effect
obtained by the activity state analysis device according to the
first embodiment of the present invention;
[0029] FIG. 2B is an explanatory view for explaining an effect
obtained by the activity state analysis device according to the
first embodiment of the present invention;
[0030] FIG. 2C is an explanatory view for explaining an effect
obtained by the activity state analysis device according to the
first embodiment of the present invention;
[0031] FIG. 2D is an explanatory view for explaining an effect
obtained by the activity state analysis device according to the
first embodiment of the present invention;
[0032] FIG. 3 is an explanatory view showing the time-series change
of an activity state in a case in which the activity state analysis
device according to the first embodiment of the present invention
is not used;
[0033] FIG. 4 is an explanatory view showing the time-series change
of an activity state in a case in which the activity state analysis
device according to the first embodiment of the present invention
is used;
[0034] FIG. 5 is a view for explaining a system using the activity
state analysis device according to the first embodiment;
[0035] FIG. 6 is a block diagram showing the arrangement of the
system using the activity state analysis device according to the
first embodiment;
[0036] FIG. 7 is a block diagram showing the arrangement of an
activity state analysis device according to the second embodiment
of the present invention;
[0037] FIG. 8 is a characteristic chart showing the time-series
change of an activity state obtained by the activity state analysis
device according to the second embodiment;
[0038] FIG. 9 is a block diagram showing the arrangement of an
activity state analysis device according to the third embodiment of
the present invention;
[0039] FIG. 10 is a characteristic chart showing the time-series
change of a statistic value concerning the heart rate of a
measurement target person obtained by the activity state analysis
device according to the third embodiment;
[0040] FIG. 11 is a block diagram showing the arrangement of
another activity state analysis device according to the third
embodiment of the present invention;
[0041] FIG. 12 is a block diagram showing the arrangement of an
activity state analysis device according to the fourth embodiment
of the present invention;
[0042] FIG. 13A is an explanatory view for explaining an effect
obtained by the activity state analysis device according to the
fourth embodiment of the present invention;
[0043] FIG. 13B is an explanatory view for explaining an effect
obtained by the activity state analysis device according to the
fourth embodiment of the present invention;
[0044] FIG. 13C is an explanatory view for explaining an effect
obtained by the activity state analysis device according to the
fourth embodiment of the present invention;
[0045] FIG. 14 is a block diagram showing the arrangement of an
activity state analysis device according to the fifth embodiment of
the present invention;
[0046] FIG. 15A is an explanatory view for explaining an effect
obtained by the activity state analysis device according to the
fifth embodiment of the present invention;
[0047] FIG. 15B is an explanatory view for explaining an effect
obtained by the activity state analysis device according to the
fifth embodiment of the present invention;
[0048] FIG. 15C is an explanatory view for explaining an effect
obtained by the activity state analysis device according to the
fifth embodiment of the present invention; and
[0049] FIG. 16 is a block diagram showing the arrangement of an
activity state analysis device according to the sixth embodiment of
the present invention.
BEST MODE FOR CARRYING OUT THE INVENTION
[0050] The embodiments of the present invention will now be
described with reference to the accompanying drawings.
First Embodiment
[0051] The arrangement of an activity state analysis device
according to the first embodiment of the present invention will be
described first with reference to FIG. 1. The activity state
analysis device includes a measurement unit 101, a tilt calculation
unit 102, a posture decision unit 103, a body motion calculation
unit 104, an activity state determination unit 105, an activity
state correction unit 106, and a time correction unit 107.
[0052] The measurement unit 101 is formed by a well-known
acceleration sensor and attached to a measurement target person to
measure acceleration. The measurement unit 101 periodically
measures accelerations in the three axis directions along X-, Y-,
and Z-axes that are orthogonal to each other at a sampling rate of,
for example, 25 Hz, thereby obtaining the time series of the
accelerations.
[0053] The tilt calculation unit 102 obtains the angle of the tilt
of the upper part of the body of the measurement target person
based on the accelerations measured by the measurement unit 101.
For example, the tilt calculation unit 102 calculates .theta. and
.PHI. by equations below as the tilts of the measurement unit 101
with respect to the gravitational accelerations of the
accelerations measured by the measurement unit 101.
[0054] Here, .theta. (-90.ltoreq..theta.<270) is the tilt of the
Z-axis of the acceleration sensor with respect to the vertical
direction, and .PHI. (-90.ltoreq. <270) is the tilt of the
X-axis of the acceleration sensor with respect to the vertical
direction. The unit is the degree [degrees].
.theta. = 180 .pi. cos - 1 ( A z A x 2 + A y 2 + A z 2 ) + 90 ( for
A y .gtoreq. 0 ) .theta. = - 180 .pi. cos - 1 ( A z A x 2 + A y 2 +
A z 2 ) + 90 ( for A y < 0 ) ( 1 ) .phi. = 180 .pi. cos - 1 ( A
x A x 2 + A y 2 + A z 2 ) + 90 ( for A y .gtoreq. 0 ) .phi. = - 180
.pi. cos - 1 ( A z A x 2 + A y 2 + A z 2 ) + 90 ( for A y < 0 )
( 2 ) ##EQU00001##
[0055] where A.sub.x, A.sub.y, and A.sub.z are accelerations in the
X-, Y-, and Z-axis directions measured by the measurement unit 101,
and the unit is the gravitational acceleration G (1.0 G.apprxeq.9.8
m/s.sup.2). In each of equations (1) and (2), the ratio of the
measurement value of a single axis with respect to the magnitude
(norm) of the composite vector of the accelerations in the X-, Y-,
and Z-axis directions measured by the measurement unit 101 is
obtained, and the inverse function of the cosine is further
obtained, thereby calculating the tilt of the measurement unit 101
as a value having the dimension of the angle.
[0056] As A.sub.x, A.sub.y, and A.sub.z in equations (1) and (2),
the output values of the measurement unit 101 may directly be
substituted. Alternatively, values obtained by applying a low-pass
filter (for example, an FIR filter or a moving average filter) for
smoothing to the output values may be used.
[0057] The posture decision unit 103 decides the posture of the
measurement target person based on the tilts of the measurement
unit 101 obtained by the tilt calculation unit 102. For example,
the posture decision unit 103 compares the values .theta. and .PHI.
calculated by equations (1) and (2) with thresholds, thereby
deciding the posture. Since the tilts of the measurement unit 101
reflect the tilts of the upper part of the body of the measurement
target person who wears the measurement unit 101, the posture of
the measurement target person can be calculated from the tilts of
the measurement unit 101.
[0058] The posture decision unit 103 decides the posture of the
measurement target person based on, for example, the following
classification.
[0059] (i) Standing position (upright): when
30.ltoreq..theta.<140.
[0060] (ii) Standing position (inverted): when .theta.<-40 or
220<.theta..
[0061] (iii) Lying position (the left side of the body is located
on the upper side): when (.PHI..ltoreq.-50, or 230<.PHI.) and
(-40.ltoreq..theta.<30), or when (.PHI..ltoreq.-50, or
230<.PHI.) and (140<.theta.<220).
[0062] (iv) Lying position (the right side of the body is located
on the upper side): when (50<.PHI.<130) and
(-40.ltoreq..theta.<30), or when (50<.PHI.<130) and
(140<.theta.<220).
[0063] (v) Lying position (lying with the face up): when
(130.ltoreq..PHI..ltoreq.230) and (-40.ltoreq..theta.<30), or
when (130.ltoreq..PHI..ltoreq.230) and (140<.theta.<220).
[0064] (vi) Lying position (lying with the face down): when
(-50.ltoreq..PHI..ltoreq.50) and (-40.ltoreq..theta.<30), or
when (-50.ltoreq..PHI..ltoreq.50) and (140<.theta.<220).
[0065] In the above-described classification conditions, the
thresholds used to determine the posture do not match the angles
(-45, 45, 135, 225) that divide the quadrants of a unit circle on
two-dimensional coordinates. This is because when a human body
stands upright, the range of motion of the back is assumed to be
large in a case of, for example, bending forward to look into
something or bending backward to look up. In the above-described
example, according to the reality of measurement values obtained by
the measurement unit 101 set on the truck, a wide calculation
region is ensured for the upright position as compared to the
measurement values for the lying positions. This method is the same
as the method of non-patent literature 1.
[0066] The above-described definitions (i) to (vi) of calculation
are set (stored) in the posture decision unit 103 as a table of
.theta. and .PHI. as shown in Table 1 below.
TABLE-US-00001 TABLE 1 ##STR00001##
[0067] The body motion calculation unit 104 obtains the magnitude
of a body motion representing the magnitude (intensity) of an
action of the measurement target person based on the accelerations
measured by the measurement unit 101.
[0068] The activity state determination unit 105 determines, based
on the posture decided by the posture decision unit 103 and the
magnitude of the body motion calculated by the body motion
calculation unit 104, whether the activity state of the measurement
target person is a first state or a second state different from the
first state. The first state is, for example, a state in which the
measurement target person gets up (rising state). In addition, the
second state is, for example, a state in which the measurement
target person is lying in the bed (lying state). A case in which
the activity state determination unit 105 time-serially obtains the
activity state representing the rising state as the first state or
the lying state as the second state will be described below as an
example.
[0069] For example, the activity state determination unit 105
determines the activity state based on the conditions to be
described below. A case in which as the grasping of the mid and
long-term activity tendency of the measurement target person, the
total time (24 hrs) of one day is identified into a rising period
that is a period during which the measurement target person is up
and a lying period that is a period during which the measurement
target person is lying in the bed will be described below.
[0070] First, if the posture is determined as a standing position
by the classifications (i) and (ii), the activity state is
classified as rising. On the other hand, if the posture is
calculated as a lying position by the classifications (iii) to
(vi), the accuracy of determination needs to be raised because, for
example, the posture may erroneously be determined as lying face
down even in a case of bending forward in the standing position. To
improve the accuracy, the lying position and the rising are
classified in consideration of the magnitude (intensity) of the
body motion obtained by the body motion calculation unit 104.
[0071] In the body motion calculation unit 104, the variance value
of time-series data of an acceleration measured by the measurement
unit 101 is used as the index of the magnitude of the body motion
by referring to the method described in patent literature 1. Let i
be a positive integer to be incremented by one by each sampling of
acceleration data from the measurement start time (i=1, 2, . . . )
For example, let a.sub.i be the value of an acceleration norm
obtained by the measurement unit 101 at an ith sampling time
t.sub.i, time-series acceleration data of 50 points be the
population, A.sub.i be the average, and S.sub.i.sup.2 be the
variance value. In this case, A.sub.i and S.sub.i.sup.2 are
represented as follows
A i = ( a i - 24 + + a i - 1 + a i + a i + 1 + + a i + 25 ) 50
##EQU00002## S i 2 = 1 50 k = - 24 25 ( a i + k - A i ) 2
##EQU00002.2##
[0072] If the variance value S.sub.i.sup.2 exceeds a predetermined
magnitude, it can be determined that a conscious body motion has
occurred, and the measurement target person has temporarily taken
the posture of bending forward in accordance with the purpose at a
high possibility. For this reason, in this case, even in the
classifications (iii) to (vi), it is determined that the
measurement target person is in the rising state, and the state is
classified as rising. For example, if (iii) to (vi) are satisfied,
and S.sub.i.sup.2.gtoreq.0.01 is satisfied, the state is determined
as the rising state. On the other hand, if
S.sub.i.sup.2.gtoreq.0.01 is not satisfied, and (iii) to (vi) are
satisfied, the state is determined as the lying state.
[0073] Based on the rising state and the lying state determined in
the above-described way, the activity state determination unit 105
performs an operation by a state function f.sub.i to be described
next, and outputs the state at the ith sampling time t.sub.i as 1
that represents the rising state or -1 that represents the lying
state.
[0074] f.sub.i=1 (when the state is determined as rising)
[0075] f.sub.i=-1 (when the state is determined as lying)
[0076] If, in the time series of the activity state obtained by the
activity state determination unit 105, the activity state
transitions from one state of the rising state and the lying state
to the other state, and the other state continues for a
predetermined time defined in advance, the activity state
correction unit 106 determines that the activity state has
transitioned from the one state to the other state. If the other
state does not continue for the predetermined time, the activity
state correction unit 106 determines that the activity state has
not transitioned from the one state to the other state.
[0077] A determination error may remain in the lying state
determined by the above-described activity state determination unit
105. For example, in a case in which the body motion unconsciously
exceeds a predetermined value by rollover or the like, a
determination error may occur in the determination of the activity
state determination unit 105. Suppressing of the determination
error is performed by the activity state correction unit 106. As
the method, the determination error is suppressed by providing a
predetermined time defined in advance as a dead band at the time of
switching of posture determination (state transition) by referring
to the past history. This can further improve the accuracy of
activity state determination.
[0078] By the following method, for example, the activity state
correction unit 106 calculates a function g.sub.i from the value of
the state function f.sub.i output from the activity state
determination unit 105 using the state functions from the state
function at the ith sampling time to the sampling time i-a back by
a from the sampling time. Here, .alpha. is 0 or a positive
integer.
[0079] g.sub.i=f.sub.i (when f.sub.i=f.sub.i-1= . . .
=f.sub.i-.alpha. holds)
[0080] g.sub.i=g.sub.i-1 (when f.sub.i=f.sub.i-1= . . .
=f.sub.i-.alpha. does not hold, that is, when at least one of the
equal signs does not hold from f.sub.i to f.sub.i-.alpha.)
[0081] For example, assume that g.sub.1=f.sub.1, and .alpha.=500.
Note that if the number of data is less than 500, .alpha. is set to
the same value as the number of data. When the sampling rate in the
measurement unit 101 is 25 Hz, g.sub.i=f.sub.i holds after the
elapse of 20 [sec] (=500/25) at the shortest from the start of the
measurement. When .alpha.=500, switching of f.sub.i is not
reflected on g.sub.i unless 20 sec do not elapse in the state after
the switching. As described above, the activity state correction
unit 106 sets the above-described time (20 sec) to the
predetermined time. If the activity state after the transition
continues for the predetermined time, the activity state correction
unit 106 determines that the transition of the activity state has
been done.
[0082] If the activity state correction unit 106 determines that
the activity state has transitioned from one state to the other
state, the time correction unit 107 sets the time returned by the
predetermined time from the time at which the activity state
correction unit 106 has determined that the activity state has
transitioned from the one state to the other state to the
transition time at which the activity state has transitioned from
the one state to the other state.
[0083] This is because in the activity state corrected by the
activity state correction unit 106, the time of transition between
the rising state and the lying state shifts (delays) by the
predetermined time. In the above-described example, the time of
transition between the rising state and the lying state delays by
20 sec. Hence, the time correction unit 107 sets the predetermined
time to the delay time, and corrects the output of the activity
state correction unit 106. The time correction unit 107 outputs,
for example, g'.sub.i=g.sub.i+.alpha. obtained by advancing the
time stamp of the time-serially obtained output g.sub.i of the
activity state correction unit 106 by 20 sec.
[0084] Effects according to the first embodiment will be described
next with reference to FIGS. 2A, 2B, 2C, and 2D. FIGS. 2A and 2B
show the time-series change of f.sub.i representing the activity
state. FIGS. 2C and 2D show the time-series change of g.sub.i
representing the corrected activity state.
[0085] FIG. 2A shows correct f.sub.i that should be the correct
answer. 1 represents the rising state, and -1 represents the lying
state. In actual measurement, however, a determination error
occurs, as shown in FIG. 2B. When the activity state correction
unit 106 corrects the time-series change of f.sub.i shown in FIG.
2B, in which the determination error occurs, g.sub.i in which the
determination error is corrected is obtained, as shown in FIG.
2C.
[0086] However, in the time-series change of g.sub.i shown in FIG.
2C, the time of switching between the rising state and the lying
state delays by the predetermined time. When this delay is
corrected by the time correction unit 107, the time-series change
of g'.sub.1, which is the same as the time-series change of f.sub.i
shown in FIG. 2A, is obtained as shown in FIG. 2D, and an activity
state according to the reality can be obtained, as is apparent.
Note that if g.sub.i is not updated due to the end of measurement
or the like, a period during which g'.sub.i is not obtained occurs.
In this case, as a substitute value, g'.sub.i=g.sub.i is set to
prevent a data loss.
[0087] An effect of the first embodiment obtained by executing
measurement for 24 hrs will be described next with reference to
FIGS. 3 and 4. In g'.sub.i, -1 is converted into 0 to save bits
used for calculation. In the output of the activity state
determination unit 105 corresponding to posture calculation
performed in the conventional technique, determination values are
dissipated due to instantaneous posture variations, as shown in
FIG. 3, and it is difficult for a general user unfamiliar to
handling of an electronic device to understand the result. Note
that referring to FIG. 3, 1 on the ordinate represents a state in
which the left side of the body faces up. 2 on the ordinate of FIG.
3 represents a state in which the right side of the body faces up.
3 on the ordinate of FIG. 3 represents a lying face down state. 4
on the ordinate of FIG. 3 represents a lying face up state.
[0088] On the other hand, according to the first embodiment, since
correction is performed by the activity state correction unit 106
and the time correction unit 107, an output in which the rising
state and the lying state can be identified at a glance can be
obtained, as shown in FIG. 4, and the state can easily be
grasped.
[0089] According to the first embodiment, correction using a dead
band in addition to the magnitude of the body motion and correction
of a delay caused by the correction are performed, thereby removing
a disturbance caused by an instantaneous change of the position. It
is therefore possible to identify 24 hrs the measurement target
person spends into the rising period and the lying period, and
appropriately grasp the activity state of the measurement target
person.
[0090] An activity state analysis method using the activity state
analysis device according to the above-described first embodiment
includes the following steps. First, the measurement unit 101
measures the acceleration in an action of the measurement target
person (first step). For example, the measurement unit 101
periodically measures accelerations in the three directions along
the X-, Y-, and Z-axes that are orthogonal to each other at a
sampling rate of, for example, 25 Hz, thereby obtaining the time
series of the accelerations. Next, the tilt calculation unit 102
obtains the angle of the tilt of the upper part of the body of the
measurement target person based on the accelerations measured by
the measurement unit 101 (first step) (second step). Next, the
posture decision unit 103 decides the posture of the measurement
target person based on the angle of tilt obtained by the tilt
calculation unit 102 (second step) (third step).
[0091] Then, the body motion calculation unit 104 obtains the
magnitude of the body motion of the measurement target person based
on the accelerations measured by the measurement unit 101 (first
step) (fourth step). Next, the activity state determination unit
105 determines, based on the posture decided by the posture
decision unit 103 (third step) and the magnitude of the body motion
calculated by the body motion calculation unit 104 (fourth step),
whether the activity state of the measurement target person is the
rising state (first state) or the lying state (second state) (fifth
step).
[0092] If, in the time series of the activity state obtained by the
activity state determination unit 105 (fifth step), the activity
state transitions from one state of the rising state and the lying
state to the other state, and the other state continues for a
predetermined time defined in advance, the activity state
correction unit 106 determines that the activity state has
transitioned from the one state to the other state. If the other
state does not continue for the predetermined time, the activity
state correction unit 106 determines that the activity state has
not transitioned from the one state to the other state (sixth
step).
[0093] Next, if the activity state correction unit 106 (sixth step)
determines that the activity state has transitioned from one state
to the other state, the time returned by the predetermined time
from the time at which it is determined that the activity state has
transitioned from the one state to the other state in the sixth
step is set to the transition time at which the activity state has
transitioned from the one state to the other state (seventh
step).
[0094] Note that the activity state analysis device according to
the above-described first embodiment is a computer device including
a CPU (Central Processing Unit), a main storage device, an external
storage device, a network connection device, and the like. The
above-described functions are implemented when the CPU operates by
a program loaded into the main storage device. Additionally, the
functions may be distributed to a plurality of computer
devices.
[0095] A system using the activity state analysis device according
to the first embodiment will be described next. For example, as
shown in FIG. 5, a sensor terminal 202 is attached to the trunk of
a measurement target person 201, and a result measured by the
sensor terminal 202 is transmitted to an external terminal 204 via
a relay terminal 203. A detection direction X of an acceleration in
the sensor terminal 202 is arranged in parallel to the
left-to-right direction of the body of the measurement target
person 201. A detection direction Y of an acceleration in the
sensor terminal 202 is arranged in parallel to the front-and-rear
direction of the body of the measurement target person 201. A
detection direction Z of an acceleration in the sensor terminal 202
is arranged in parallel to the up-and-down direction of the body of
the measurement target person 201.
[0096] As shown in FIG. 6, the sensor terminal 202 includes an
acceleration sensor 301, a detection unit 302, a storage unit 303,
an analysis unit 304, a transmission processing unit 305, and a
communication interface 306. The relay terminal 203 includes a
communication interface 311, a reception processing unit 312, a
storage unit 313, an analysis unit 314, a transmission processing
unit 315, and a communication interface 316. The external terminal
204 includes a communication interface 321, a reception processing
unit 322, a storage unit 323, an analysis unit 324, a control unit
325, and an operation device 326.
[0097] The acceleration sensor 301 measures accelerations in the
three directions along the X-, Y-, and Z-axes that are orthogonal
to each other. The detection unit 302 converts the analog
acceleration signal measured by the acceleration sensor 301 into
digital acceleration data at a predetermined sampling rate and
outputs it. The measurement unit 101 according to the
above-described embodiment corresponds to the acceleration sensor
301. The storage unit 303 stores the acceleration data digitized by
the detection unit 302. The analysis unit 304 obtains an activity
state based on the acceleration data stored in the storage unit
303, and the like. The tilt calculation unit 102, the body motion
calculation unit 104, the posture decision unit 103, the activity
state determination unit 105, the activity state correction unit
106, and the time correction unit 107 according to the
above-described embodiment are included in the analysis unit
304.
[0098] The transmission processing unit 305 transmits the
acceleration data stored in the storage unit 303, and the like to
the relay terminal 203 via the communication interface 306. The
communication interface 306 is formed by an operation interface and
an antenna corresponding to a wireless data communication standard
such as LTE (Long Term Evolution), third generation mobile
communication system, wireless LAN (Local Area Network), or
Bluetooth.RTM..
[0099] The relay terminal 203 is formed from the communication
interface 311 that receives data transmitted from the sensor
terminal 202, the reception processing unit 312, the storage unit
313, the analysis unit 314, the transmission processing unit 315,
and the communication interface 316 that transmits data to the
external terminal 204.
[0100] The external terminal 204 includes the communication
interface 321 that receives data transmitted from the relay
terminal 203, the reception processing unit 322, the storage unit
323, the analysis unit 324, and the control unit 325 that instructs
an operation instruction to the operation device 326 that operates
based on analyzed data.
[0101] Based on information stored in the storage unit 323, the
control unit 325 causes the operation device 326 to execute an
operation to assist the measurement target person.
[0102] The operation device 326 is a video output device (a monitor
or the like), a voice output device (a speaker, a musical
instrument, or the like), a light source (an LED (Light Emitting
Diode) or an electric bulb), an actuator (a vibrator, a robot arm,
or an electrotherapeutic instrument), a cooling/heating device (a
heater or a Peltier element), or the like.
[0103] Not all of the analysis unit 304 of the sensor terminal 202,
the analysis unit 314 of the relay terminal 203, and the analysis
unit 324 of the external terminal 204 need be arranged, and only
one or two of them may be provided. In addition, analysis
processing may be distributed to the analysis unit 304, the
analysis unit 314, and the analysis unit 324 in accordance with the
steps of the activity state analysis method according to the first
embodiment.
[0104] The result by g'.sub.i shown in FIG. 2D is presented by the
operation device 326 of the external terminal 204. In addition, the
operation device 326 not only presents the above-described activity
state analysis result but also makes a signal by a sound,
vibration, contact, heat, coldness, or the like to the measurement
target person or the user of the external terminal 204 when
switching of the activity state has occurred, thereby notifying the
change of the activity state.
Second Embodiment
[0105] The second embodiment of the present invention will be
described next with reference to FIG. 7. FIG. 7 is a block diagram
showing the arrangement of an activity state analysis device
according to the second embodiment of the present invention. The
activity state analysis device includes a measurement unit 101, a
tilt calculation unit 102, a posture decision unit 103, a body
motion calculation unit 104, an activity state determination unit
105, an activity state correction unit 106, and a time correction
unit 107. These components are the same as in the above-described
first embodiment.
[0106] The activity state analysis device according to the second
embodiment includes a walking pace calculation unit 108 and a
walking period specifying unit 109 in addition to the
above-described components.
[0107] The walking pace calculation unit 108 obtains the walking
pace of a measurement target person based on the acceleration
measured by the measurement unit 101. The walking pace calculation
unit 108 obtains the walking pace of the measurement target person
based on the time-series data of the acceleration measured by the
measurement unit 101. For example, the acceleration at a standstill
is about 1 G. As a feature, the time-rate change of the
acceleration in a walking state or a running state exhibits a
vibration waveform with respect to 1 G as the center. Using this
feature, a lower threshold and an upper threshold are set to 0.9 G
and 1.1 G, respectively. A timing at which the acceleration is less
than the lower threshold or a timing at which the acceleration is
more than the upper threshold is detected from the obtained
time-series data of the acceleration. If two timing detections
occur within, for example, 1 sec, it is determined that a walking
action has occurred, and one step is counted. In addition, when
conversion is performed to obtain the number of times of counting
that has occurred in a unit time, the walking pace (spm) can be
obtained (see patent literature 1).
[0108] Based on the walking pace of the measurement target person
obtained by the walking pace calculation unit 108, the walking
period specifying unit 109 specifies the period of the walking
state in which the measurement target person has walked in the
period of the rising state (first state) defined by the transition
time corrected by the time correction unit 107. For example, the
walking period specifying unit 109 specifies, as the period of the
walking state, a period during which the walking pace measured by
the walking pace calculation unit 108 exceeds 15 spm in the period
of rising. Note that in the second embodiment, running is included
in walking.
[0109] In an activity state analysis method according to the second
embodiment, the following steps are added to the steps of the
activity state analysis method using the activity state analysis
device according to the above-described first embodiment.
[0110] First, the walking pace calculation unit 108 obtains the
walking pace of the measurement target person based on the
acceleration measured by the measurement unit 101 (first step)
(eighth step). Next, the walking period specifying unit 109
specifies, based on the walking pace of the measurement target
person obtained by the walking pace calculation unit 108 (eighth
step), the period of the walking state in which the measurement
target person has walked in the period of the rising state defined
by the transition time corrected by the time correction unit 107
(seventh step) (ninth step).
[0111] According to the above-described second embodiment, the
activity state is time-serially obtained, as shown in FIG. 8. As
shown in FIG. 8, the walking period specifying unit 109 outputs 2
as the walking state. Note that (b) of FIG. 8 shows an enlarged
view of a part in (a) of FIG. 8. According to the second
embodiment, the walking state is independently shown, as shown in
FIG. 8. As described above, according to the second embodiment, it
is possible to grasp, at a glance, for example, a period in which
the measurement target person is not only rising but also the
walking frequency is high.
Third Embodiment
[0112] The third embodiment of the present invention will be
described next with reference to FIG. 9. FIG. 9 is a block diagram
showing the arrangement of an activity state analysis device
according to the third embodiment of the present invention. The
activity state analysis device includes a measurement unit 101, a
tilt calculation unit 102, a posture decision unit 103, a body
motion calculation unit 104, an activity state determination unit
105, an activity state correction unit 106, and a time correction
unit 107. These components are the same as in the above-described
first embodiment.
[0113] The activity state analysis device according to the third
embodiment includes an electrocardiographic unit 111, a heartbeat
calculation unit 112, and a statistic value calculation unit 113 in
addition to the above-described components. The
electrocardiographic unit 111 and the heartbeat calculation unit
112 form a physical information measurement unit.
[0114] The electrocardiographic unit 111 measures the electrical
information (cardiac potential) of the heart of a measurement
target person. The heartbeat calculation unit 112 calculates at
least one of a heartbeat interval (RRI) and a heart rate from the
measurement value measured by the electrocardiographic unit 111. In
the third embodiment, the heartbeat interval and the heart rate are
obtained as physical information.
[0115] The statistic value calculation unit 113 obtains a statistic
value including at least one of the average value, the median, the
maximum value, the minimum value, the standard deviation, the 75%
level value, and the 25% level value of at least one of the
heartbeat interval and the heart rate obtained by the heartbeat
calculation unit 112. The statistic value calculation unit 113
obtains the statistic value based on an activity state defined by
the transition time corrected by the time correction unit 107. The
statistic value calculation unit 113 obtains the statistic value
for each of states such as lying and rising in the activity state
corrected by the time correction unit 107.
[0116] In an activity state analysis method according to the third
embodiment, the following steps are added to the steps of the
activity state analysis method using the activity state analysis
device according to the above-described first embodiment.
[0117] First, the physical information of the measurement target
person is measured (10th step). More specifically, the
electrocardiographic unit 111 measures the electrical activity of
the heart of the measurement target person, and the heartbeat
calculation unit 112 calculates, as physical information, at least
one of the heartbeat interval and the heart rate from the
measurement value measured by the electrocardiographic unit 111.
Next, based on the activity state defined by the transition time
corrected in the seventh step, the statistic value calculation unit
113 obtains a statistic value including at least one of the average
value, the median, the maximum value, the minimum value, the
standard deviation, the 75% level value, and the 25% level value of
at least one of the heartbeat interval and the heart rate obtained
by the heartbeat calculation unit 112 (11th step).
[0118] According to the above-described third embodiment, the
statistic value can be grasped time-serially, as shown in FIG. 10.
FIG. 10 shows a rising state (full circles) and a lying state (full
squares) as activity states. FIG. 10 also shows the statistic
values of the heart rate in these states. As the statistic value,
the average vale is indicated by a point of a full circle or a full
square. The error bar on the upper side represents the maximum
value, and the error bar on the lower side represents the minimum
value.
[0119] In this way, analysis based on the activity state can be
performed each day. When the measurement is performed for a long
term, it is possible to easily grasp, based on the activity state,
the sign of recovery of a disease, a load given to the body by a
seasonal change, a change in conditions caused by an exercise
habit, or the like. In addition, when the above-described result is
fed back, it can contribute to lifestyle investigations or
improvement of lifestyle.
[0120] A motion intensity may be used in place of the heart rate.
For example, as shown in FIG. 11, a motion intensity calculation
unit 114 is provided to calculate a motion intensity from the heart
rate calculated by the heartbeat calculation unit 112. The motion
intensity is obtained by (measured heart rate-resting heart rate of
measurement target person)+(maximum heart rate of measurement
target person-resting heart rate) (see non-patent literature 3).
Note that the maximum heart rate of the measurement target person
is set to 220-(age of measurement target person). In addition, the
resting heart rate of the measurement target person is set to 60.
The maximum heart rate of the measurement target person and the
resting heart rate of the measurement target person may be actually
measured in advance. For example, as the resting heart rate, the
heart rate during a period in which the measurement target person
is sitting quietly is used. Alternatively, the average value, the
median, or the minimum value may be obtained from the heart rate
during the lying period of the previous day or during the lying
period of the previous night (0:00 to 5:00) and used as the resting
heart rate.
[0121] A statistic value calculation unit 113a obtains a statistic
value including at least one of the average value, the median, the
maximum value, the minimum value, the standard deviation, the 75%
level value, and the 25% level value of the motion intensity
obtained by the motion intensity calculation unit 114. The
statistic value calculation unit 113a obtains the above-described
statistic value based on the activity state defined by the
transition time corrected by the time correction unit 107. The
statistic value calculation unit 113a obtains the statistic value
for each of states such as lying and rising in the activity state
corrected by the time correction unit 107.
[0122] In the activity state analysis method in this case, the
following steps are added to the steps of the activity state
analysis method using the activity state analysis device according
to the above-described first embodiment.
[0123] First, the electrocardiographic unit 111 measures the
electrical activity of the heart of the measurement target person
(10th step). Next, the heartbeat calculation unit 112 calculates
the heart rate from the measurement value measured by the
electrocardiographic unit 111 (10th step) (11th step). Next, the
motion intensity calculation unit 114 calculates the motion
intensity based in the heart rate obtained by the heartbeat
calculation unit 112 (11th step) (12th step). Next, the statistic
value calculation unit 113a obtains a statistic value including at
least one of the average value, the median, the maximum value, the
minimum value, the standard deviation, the 75% level value, and the
25% level value of the motion intensity obtained by the motion
intensity calculation unit 114 (12th step) based on the activity
state defined by the transition time corrected in the seventh step
(13th step).
[0124] Even when the statistic value is time-serially grasped for
the motion intensity in this way, analysis based on the activity
state can be performed each day, as described above. When the
measurement is performed for a long term, it is possible to easily
grasp, based on the activity state, the sign of recovery of a
disease, a load given to the body by a seasonal change, a change in
conditions caused by an exercise habit, or the like. In addition,
when the above-described result is fed back, it can contribute to
lifestyle investigations or improvement of lifestyle.
[0125] In addition, the physical information may be a heart rate
measured by a pulse measurement unit that measures the physical
contraction of the pulse of the measurement target person. The
physical information may be a respiratory state measured by an
impedance measurement unit that measures the impedance of the body
of the measurement target person, thereby measuring the respiratory
state. The physical information may be a blood pressure measured by
a blood pressure measurement unit that measures the blood pressure
of the measurement target person. The physical information may be a
body temperature measured by a body temperature measurement unit
that measures the body temperature of the measurement target
person. The physical information may be a muscle potential measured
by an electromyographic unit that measures the muscle potential of
the measurement target person. The physical information may be a
body weight measured by a body weight measurement unit that
measures the body weight of the measurement target person.
[0126] In addition, the physical information may be a calorie
consumption measured by a calorie measurement unit that measures
the calorie consumption of the measurement target person. The
physical information may be an activity or sleeping action measured
by an activity measurement unit that measures the activity or
sleeping action of the measurement target person by an
electroencephalograph or an acceleration sensor. The physical
information may be sweating measured by a sweating measurement unit
that measures the sweating of the measurement target person.
Fourth Embodiment
[0127] The fourth embodiment of the present invention will be
described next with reference to FIG. 12. An activity state
analysis device includes a measurement unit 101, a tilt calculation
unit 102, a posture decision unit 103, a body motion calculation
unit 104, an activity state determination unit 105, an activity
state correction unit 106, a time correction unit 107, a walking
pace calculation unit 108, and a walking period specifying unit
109. These components are the same as in the above-described second
embodiment.
[0128] The activity state analysis device according to the fourth
embodiment includes a data adjustment unit 115 in addition to the
above-described components. The data adjustment unit 115
down-samples the time-serially obtained data of the activity state
including a rising state (first state) and a lying state (second
state), which are time-serially obtained, while assigning priority
to each state. In the fourth embodiment, a walking state is also
included in the activity state. The data of the activity state is a
time series whose time is corrected by the time correction unit
107, and is formed by the data of the rising state and the lying
state determined by the activity state determination unit 105 and
corrected by the activity state correction unit 106 and the walking
state specified by the walking period specifying unit 109. When
down-sampling is performed by the data adjustment unit 115, the
number of data of the activity state can be reduced by
thinning.
[0129] The data adjustment unit 115 down-samples, for example, data
per sec at an interval of 1 min. In this down-sampling processing,
the data adjustment unit 115 assigns priority to each of walking,
rising, and lying, and gives high priority of walking.
[0130] The data adjustment unit 115 holds the data of the activity
state obtained at an interval of, for example, 1 sec for 1 min (60
points). Next, if walking is determined continuously for 6 sec (6
points) in the period of 1 min of holding, the data adjustment unit
115 decides the data of one point after the down-sampling as
walking. Note that the continuation time for the determination is
not limited to 6 sec. However, 6 sec is a time necessary for an
able-bodied person to walk about 10 steps, or for an elderly
patient to walk about six steps. This is appropriate because
walking shifted to a side a little can be excluded. If the walking
state is not obtained continuously for 6 sec, the data adjustment
unit 115 employs a longer one of the rising and lying included in 1
min as the data of 1 point after down-sampling. If the rising and
lying have the same point (time), the data adjustment unit 115
gives priority to rising.
[0131] In an activity state analysis method according to the fourth
embodiment, the following step is added to the steps of the
activity state analysis method using the activity state analysis
device according to the above-described second embodiment. The data
adjustment unit 115 down-samples the time-serially obtained data of
the activity state.
[0132] Effects according to the third embodiment will be described
with reference to FIGS. 13A, 13B, and 13C. FIG. 13A shows the
time-series data of an activity state before down-sampling. FIG.
13B shows the result of down-sampling at an interval of 1 min by
the data adjustment unit 115. FIG. 13C shows a down-sampling result
obtained when data is extracted mechanically once in 60 times from
the data per sec.
[0133] Walking requires the physical strength of the measurement
target person, unlike rising and lying. Hence, the walking state is
poor in continuity. For this reason, if down-sampling is
mechanically performed, the information of walking may be lost, as
shown in FIG. 13C. In the result shown in FIG. 13C, the walking
state is lost, as is apparent from comparison with FIG. 13A.
[0134] On the other hand, according to the fourth embodiment,
down-sampling is performed while assigning priority to each state.
As shown in FIG. 13B, down-sampling can be performed in a state in
which the loss of the walking state is reduced. As a result,
according to the fourth embodiment, it is possible to efficiently
use the time-serially obtained data of the activity state and avoid
the resource of a CPU or a memory from being oppressed at the time
of data presentation.
Fifth Embodiment
[0135] The fifth embodiment of the present invention will be
described next with reference to FIG. 14. An activity state
analysis device includes a measurement unit 101, a tilt calculation
unit 102, a posture decision unit 103, a body motion calculation
unit 104, an activity state determination unit 105, an activity
state correction unit 106, a time correction unit 107, a walking
pace calculation unit 108, a walking period specifying unit 109,
and a data adjustment unit 115. These components are the same as in
the above-described fourth embodiment.
[0136] The activity state analysis device according to the fifth
embodiment includes a data additional adjustment unit 116 in
addition to the above-described components. The data additional
adjustment unit 116 further down-samples the time-series data of an
activity state output from the data adjustment unit 115 while
assigning priority to each state. In the fifth embodiment as well,
a walking state is included in the activity state. The data of the
activity state is a time series whose time is corrected by the time
correction unit 107, and is formed by the data of the rising state
and the lying state determined by the activity state determination
unit 105 and corrected by the activity state correction unit 106
and the walking state specified by the walking period specifying
unit 109. When the data of the activity state down-sampled by the
data adjustment unit 115 is further down-sampled by the data
additional adjustment unit 116, the number of data of the activity
state can further be reduced by thinning.
[0137] The data additional adjustment unit 116 down-samples, at an
interval of 30 min, the data of the activity state obtained by the
data adjustment unit 115 at an interval of 1 min, thereby
time-serially extracting 1 point in every 30 points. When executing
the down-sampling again in this way, if walking is included 10
points or more, the data additional adjustment unit 116 gives
priority to this, and this portion is determined as the walking
state in the result of down-sampling at an interval of 30 min. This
is because if walking is done for about 1/3 of the period, leaving
the walking as a history is intuitively appropriate for a life-log.
If walking is not included, one of rising and lying with a higher
occurrence frequency is given priority.
[0138] Effects according to this embodiment will be described with
reference to FIGS. 15A, 15B, and 15C. FIG. 15A shows the
time-series data of an activity state before down-sampling by the
data adjustment unit 115 and the data additional adjustment unit
116. FIG. 15B shows the result of down-sampling at an interval of 1
min by the data adjustment unit 115 and then down-sampling at an
interval of 30 min by the data additional adjustment unit 116. FIG.
15C shows the result of down-sampling at an interval of 30 min by
the data adjustment unit 115.
[0139] Referring to FIGS. 15B and 15C, almost the same extraction
results are obtained. In a case in which the data additional
adjustment unit 116 performs down-sampling at an interval of 30
min, since data down-sampled (thinned) at an interval of 1 min is
down-sampled (thinned) at an interval of 30 min, a light operation
suffices. To the contrary, in a case in which the data adjustment
unit 115 performs down-sampling at an interval of 30 min, data per
sec needs to be stored for 30 min. This applies a load to
arithmetic processing (the CPU or memory is oppressed) in a
real-time operation. According to the fifth embodiment, it is
possible to implement down-sampling by an operation of little
load.
Sixth Embodiment
[0140] The sixth embodiment of the present invention will be
described next with reference to FIG. 16. An activity state
analysis device includes a measurement unit 101, a tilt calculation
unit 102, a posture decision unit 103, a body motion calculation
unit 104, an activity state determination unit 105, an activity
state correction unit 106, and a time correction unit 107. These
components are the same as in the above-described first embodiment.
The activity state analysis device according to the sixth
embodiment includes a data adjustment unit 117 and a data
additional adjustment unit 118 in addition to the above-described
components.
[0141] The data adjustment unit 117 down-samples the time-serially
obtained data of the activity state including a rising state (first
state) and a lying state (second state), which are time-serially
obtained, while assigning priority to each state. The data
adjustment unit 117 down-samples, for example, data per sec at an
interval of 1 min. In this down-sampling processing, the data
adjustment unit 117 assigns priority to each of rising and lying.
If the rising and lying have the same point (time), the data
adjustment unit 117 gives priority to rising.
[0142] The data additional adjustment unit 118 further down-samples
the time-series data of an activity state output from the data
adjustment unit 117 while assigning priority to each state.
[0143] The data of the activity state is a time series whose time
is corrected by the time correction unit 107, and is formed by the
rising state and the lying state determined by the activity state
determination unit 105 and corrected by the activity state
correction unit 106. When the data adjustment unit 117 and the data
additional adjustment unit 118 perform down-sampling, the number of
data of the activity state can be reduced by thinning.
[0144] For example, in a situation in which a person can hardly
walk immediately after an operation in a hospital, walking
determination is unnecessary. In addition, since the body load is
different between lying in which a person yields himself/herself to
gravity and rising in which he/she rises against gravity, an
application purpose focusing only on rising and lying can also be
considered. In this case, as described above, the rising state and
the lying state, which are time-serially obtained, are set to the
target, and the number of data of the activity state is reduced by
thinning.
[0145] As described above, according to the present invention, in
addition to the magnitude of a body motion obtained by the body
motion calculation unit, the activity state correction unit
performs correction by providing a dead band, and the time
correction unit corrects a delay caused by the correction. It is
therefore possible to more correctly measure the activity state of
the measurement target person with focus on the lifestyle.
[0146] Note that the present invention is not limited to the
above-described embodiments, and many modification and combinations
can be made by a person who has normal knowledge in the field
without departing from the technical scope of the present
invention. For example, the second embodiment and the third
embodiment may be combined, as a matter of course. In addition, the
first state may be a standing state, and the second state may be a
sitting state.
EXPLANATION OF THE REFERENCE NUMERALS AND SIGNS
[0147] 101 . . . measurement unit, 102 . . . tilt calculation unit,
103 . . . posture decision unit, 104 . . . body motion calculation
unit, 105 . . . activity state determination unit, 106 . . .
activity state correction unit, 107 . . . time correction unit
* * * * *
References